Adaptive Resolution Management Using Sub-Frame Scaling
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Solution Overview
Problem
Current video compression technologies face challenges in managing resolution efficiently, leading to increased bitrates and costs due to the requirement of re-coding and re-sending whole portions of video, such as group-of-pictures (GOP), which can result in higher costs and lower video quality.
Innovation Solution
Adaptive Resolution Management (ARM) allows for flexible video encoding and decoding by using reference frames of different resolutions than predicted frames, enabling downscaling or upscaling of video resolution, thus reducing bitrate and improving playback characteristics, by employing rescaling constants and spatial filters for sub-frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If whole portions of video (GOP) are re-coded and re-sent for resolution management, then resolution can be managed, but bitrate increases and costs increase
Solution Approach 1:
The video frame is divided into multiple sub-frames, each of which can be independently scaled using different scaling constants. This allows selective resolution management at the sub-frame level rather than requiring re-coding of entire GOP structures, thereby reducing bitrate while maintaining resolution control.
Solution Approach 2:
Different scaling constants are applied to different sub-frames within the same frame based on local quality requirements. This enables precise resolution management for specific regions without affecting the entire video stream, avoiding unnecessary bitrate increases.
2Manufacturing precision
If whole portions of video (GOP) are re-coded and re-sent for resolution management, then resolution can be managed, but costs increase
Solution Approach 1:
By segmenting the frame into sub-frames with independent scaling, the system avoids the expensive operation of re-coding entire GOP structures. The segmentation enables lightweight, localized resolution adjustments that are computationally efficient and cost-effective.
Solution Approach 2:
The invention changes the parameter being managed from entire GOP re-coding to sub-frame scaling constants. This parameter change reduces computational complexity and processing costs while achieving the same resolution management objective.
3Quantity of substance
If reference frames of different resolutions are used for encoding, then bitrate is reduced and compression efficiency is improved, but complexity of encoding and decoding algorithms increases
Solution Approach 1:
The scaling constants are dynamically determined for each sub-frame based on motion characteristics and content analysis. This dynamic approach enables adaptive bitrate reduction while managing complexity through systematic decision-making rather than exhaustive processing.
Solution Approach 2:
The encoding system automatically determines appropriate scaling constants for each sub-frame based on local characteristics, eliminating the need for complex manual configuration or centralized control. The system serves itself by making local decisions that optimize bitrate while controlling complexity.
Data Source
AI summary
A video encoder encodes a bitstream for decoding by a compliant decoder which is configured to selectively operate in a mode for generating a motion compensation predictor from a reference picture for a subsequent picture having a resolution different from the reference picture. The encoded bitstream includes a coded picture having a first coded region and a second coded region and signaling information from which the decoder determines first and second spatial resolution scale factors for reconstructing the first and second regions.